Compare list/dict; parse JSON/CSV at scale

Q: Compare list/dict; parse JSON/CSV at scale

This is a Data Manipulation (SQL/Python) interview question from Thumbtack for Data Scientist roles. View the full question and solution on PracHub.

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Question

Compare Python list and dict precisely: for append/insert/lookup/update/delete, state average and worst-case time complexity, memory implications, and ordering guarantees in CPython 3. How would you store and retrieve values in each (show concise code for appending to a list and updating a dict)? Define JSON vs. CSV and when you would choose JSON over CSV (consider nesting, schema evolution, interoperability, compression). Show exact Python code to stream-read both formats: (a) JSON Lines file via iterating line-by-line and json.loads; (b) CSV via csv.DictReader; and (c) pandas read_csv with chunksize to compute the sum of a numeric column 'value' in data.csv without exceeding memory. Explain how you would handle malformed rows, missing/NaN values, bad encodings, and numeric overflow; propose chunk-size heuristics for a 10 GB file on a 16 GB RAM machine; and provide a non-pandas alternative that still streams safely.

Compare list/dict; parse JSON/CSV at scale

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